Insurance is used to mitigate risk, and the price or even availability of insurance can depend on the risk associated with what is being insured. Insurance companies may evaluate a number of different data in determining whether to offer insurance to a particular customer, and if offered, how much to charge. In the vehicle insurance area, traditional factors may include historical claim history, driving record, gender, age, type of vehicle, and vehicle value. Much of this data is generally referred to herein as “traditional insurance factors”, and generally excludes information relating to the history of a specific vehicle being insured, or being considered for insurance.
Statistical analysis over many years of tracking insurance policies has shown that the existence of certain traditional insurance factors has value in predicting the risk associated with certain drivers and vehicles, including both the frequency of a future loss event, and the severity of that future loss event. For example, statistical analysis might show that there is greater risk of loss incurred in insuring a sports car driven by a teen age boy with multiple speeding tickets than there is in insuring a minivan driven by a middle aged woman with no moving violations. Thus, an insurance company may decide to not even offer insurance to the teen age driver, or if it does, to offer it at a much higher cost. Insurance companies evaluate multiple variables and factors to determine risk, and more accurate evaluations of risk improve the ability of insurance companies to maintain profitability by pricing and/or underwriting risk more accurately and appropriately, as well as to tailor product eligibility for specific individuals.
“Risk” is often viewed as a combination of predicted frequency and severity, where “frequency” predicts the probability that a loss event will occur within a given timeframe, and “severity” predicts the loss cost in dollars of that particular event. In the insurance industry, “severity” is routinely calculated by dividing loss dollars for a given timeframe by the number of claims within that same timeframe. Breaking risk down into different components can enable a better understanding of the risk, and that can help to improve the estimation of risk for a given situation. A better understanding of risk can lead to better correlations of risk to cost, which can minimize instances of mistakenly overcharging or undercharging for insurance. This can lead to better or more predictable profits for insurance companies, and ultimately more appropriate rates for consumers.
Insurance companies typically analyze historical carrier loss and premium data to create statistical models that estimate risk based primarily or entirely on that analysis. These models are used to assess expected risk. That assessment can be used by an insurance company to determine if a policy should be issued, or if it is issued, what rate should be charged for that policy. However, many insurance companies may have different determinations as to which traditional insurance factors (or data) have the greatest impact (or largest predictive value) on their customers, and thus a multitude of models can be used across insurance companies. Insurance companies use specific industry terms to describe and communicate insurance-related concepts. Knowledge of these terms can aid in understanding discussions of insurance policies and considerations. A few of these terms are defined below.
“Loss dollars” means actual dollars paid by an insurance carrier due to a claim or a group of claims incurred by a particular risk group.
“Earned premium” can be defined as the amount of total premiums collected by an insurance company over a period of time that have been earned based on the ratio of the time passed on the policies to their effective life. This pro-rated amount of paid-in-advance premiums have been “earned” and now belong to the insurer. For instance, if a person was two months into a six month policy that was paid for in advance, there would be approximately two months of earned premium for the insurance company. The remaining four months of premium is called unearned premium.
“Loss ratio” means the loss dollars divided by the earned premium. This is typically expressed as a decimal or a percentage. This number is indicative of financial performance, and many carriers calculate a maximum acceptable loss ratio to support some defined profit margin. Ratios higher than this maximum indicate either a loss or a reduced profit margin.
“Pure premium” means the total premium that is needed to pay expected losses, and is normally calculated by multiplying frequency by severity (discussed further below). Pure premium differs from Loss Ratio in that it does not convey financial performance as it is simply the amount of loss dollars paid irrespective of whether this is done at a profit or loss to the carrier.
“Nonstandard risk” is an automobile insurance driver market characterization or classification based on high risk designations, typically associated with some combination of the following characteristics: no prior automobile insurance, selection of minimum Bodily Injury (BI) coverage limits, and/or presence of significant driving violations (i.e. DUI, multiple accidents or speeds, etc.).
“Standard/Preferred risk” is an automobile insurance driver market characterization or classification based on low to moderate risk designations, typically associated with some combination of the following characteristics: lengthy history of prior automobile insurance, selection of greater than minimum Bodily Injury (BI) coverage limits, and/or clean driving record with few, if any, driving violations.
“Vehicle symbol” is an automobile insurance rating variable for both liability and physical damage coverage that characterizes vehicle risk associated with the make, model, trim level, and sometimes model year of a particular vehicle (i.e. 2010 Ford Mustang GT convertible). These symbols can be developed internally as proprietary to an insurer or they can be purchased from large data aggregators (i.e. ISO).
“Underwriting” is typically defined as the process where an insurance company decides whether or where it is willing to place a risk within that company's product offerings. Underwriting decisions can include whether or not to accept a risk as a customer. If a company opts to insure a customer, additional underwriting can be used to determine what insurance program or product the customer is eligible for, or even what specific coverage features or options within a program or product that customer is eligible for.
“Rating” is the process where an insurance company utilizes risk characteristics to determine the amount to charge a customer for insurance.
In evaluating the risk associated with a particular policy, insurance companies have not historically considered or evaluated detailed information on the unique history specific to each individual vehicle (at a 17 digit Vehicle Identification Number level for vehicles with a model year of 1981 or newer) being insured or considered for insurance. Consequently, a need exists for a system and method for analyzing risk using vehicle history data for a specific individual vehicle.